Introduction to Scientific Computing in Python

Introduction to Scientific Computing in Python

A set of lectures on scientific computing with Python, using IPython notebooks.

Tag(s): Python

Publication date: 16 Apr 2016

ISBN-10: n/a

ISBN-13: n/a

Paperback: 177 pages

Views: 10,426

Type: Lecture Notes

Publisher: n/a

License: Creative Commons Attribution 3.0 Unported

Post time: 24 Sep 2016 04:00:00

Introduction to Scientific Computing in Python

Introduction to Scientific Computing in Python A set of lectures on scientific computing with Python, using IPython notebooks.
Tag(s): Python
Publication date: 16 Apr 2016
ISBN-10: n/a
ISBN-13: n/a
Paperback: 177 pages
Views: 10,426
Document Type: Lecture Notes
Publisher: n/a
License: Creative Commons Attribution 3.0 Unported
Post time: 24 Sep 2016 04:00:00
Summary/Excerpts of (and not a substitute for) the Creative Commons Attribution 3.0 Unported:
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Table of Contents:

1. Introduction to scientific computing with Python
2. Introduction to Python programming
3. Numpy - multidimensional data arrays
4. SciPy - Library of scientific algorithms for Python
5. matplotlib - 2D and 3D plotting in Python
6. Sympy - Symbolic algebra in Python
7. Using Fortran and C code with Python
8. Lecture 6B - Tools for high-performance computing applications
9. Revision control software

The latest version of this IPython notebook lecture is available here.




About The Author(s)


J. Robert Johansson, Ph.D. works with theoretical and computational solid-state physics, with focus on quantum mechanics in superconducting electrical circuits. He has worked on qubits for quantum computing, artificial-atom and resonator circuits for on-chip atomic and quantum-optics-like physics in the microwave regime, and on quantum vacuum related phenomena, such as the dynamical Casimir effect.

Robert Johansson

J. Robert Johansson, Ph.D. works with theoretical and computational solid-state physics, with focus on quantum mechanics in superconducting electrical circuits. He has worked on qubits for quantum computing, artificial-atom and resonator circuits for on-chip atomic and quantum-optics-like physics in the microwave regime, and on quantum vacuum related phenomena, such as the dynamical Casimir effect.


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